Triple

T7901900
Position Surface form Disambiguated ID Type / Status
Subject Lagrangian-history direct interaction approximation E183471 entity
Predicate extends P1244 FINISHED
Object direct interaction approximation E183470 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: direct interaction approximation | Statement: [Lagrangian-history direct interaction approximation, extends, direct interaction approximation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: direct interaction approximation
Context triple: [Lagrangian-history direct interaction approximation, extends, direct interaction approximation]
  • A. direct interaction approximation (DIA) chosen
    The direct interaction approximation (DIA) is a statistical closure theory in turbulence developed by Robert Kraichnan that models the nonlinear interactions among fluctuating velocity fields to predict turbulent flow properties.
  • B. Lagrangian-history direct interaction approximation (LHDIA)
    Lagrangian-history direct interaction approximation (LHDIA) is a turbulence theory framework that models fluid particle dynamics by tracking their Lagrangian histories to more accurately capture nonlinear interactions and temporal correlations in turbulent flows.
  • C. Gutzwiller approximation
    The Gutzwiller approximation is a variational method in condensed matter physics used to study strongly correlated electron systems, particularly metal–insulator (Mott) transitions in lattice models like the Hubbard model.
  • D. Kirkwood approximation in statistical mechanics
    The Kirkwood approximation in statistical mechanics is a method for approximating many-particle correlation functions by expressing higher-order correlations in terms of lower-order ones, simplifying the description of interacting particle systems.
  • E. Bogoliubov–Born–Green–Kirkwood–Yvon hierarchy
    The Bogoliubov–Born–Green–Kirkwood–Yvon hierarchy is a set of coupled equations in statistical mechanics that describes the time evolution of reduced distribution functions for many-particle systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca828d13088190b222be7aa9f9315c completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a40a0508190864479c2c41b12cb completed March 31, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bbd93348190883c6152f18f8214 completed March 31, 2026, 5:29 a.m.
Created at: March 30, 2026, 5:02 p.m.